Cross-cultural Mood Perception in Pop Songs and its Alignment with Mood Detection Algorithms
Harin Lee, Frank Hoeger, Marc Schoenwiesner, Minsu Park, Nori Jacoby

TL;DR
This study compares cross-cultural human perceptions of music mood with automated mood detection algorithms, finding high agreement on basic moods across cultures and no bias in algorithms, supporting their objectivity in popular music.
Contribution
It provides a cross-cultural analysis of mood perception in music and evaluates the cultural bias of mood detection algorithms, demonstrating their robustness across diverse populations.
Findings
High similarity in basic mood ratings across cultures
Significant differences in complex mood perceptions
Algorithms show no cultural bias in mood detection
Abstract
Do people from different cultural backgrounds perceive the mood in music the same way? How closely do human ratings across different cultures approximate automatic mood detection algorithms that are often trained on corpora of predominantly Western popular music? Analyzing 166 participants responses from Brazil, South Korea, and the US, we examined the similarity between the ratings of nine categories of perceived moods in music and estimated their alignment with four popular mood detection algorithms. We created a dataset of 360 recent pop songs drawn from major music charts of the countries and constructed semantically identical mood descriptors across English, Korean, and Portuguese languages. Multiple participants from the three countries rated their familiarity, preference, and perceived moods for a given song. Ratings were highly similar within and across cultures for basic mood…
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Taxonomy
TopicsNeuroscience and Music Perception · Music and Audio Processing · Emotion and Mood Recognition
